绘制每个日期的出现次数

本文介绍了绘制每个日期的出现次数的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我对熊猫数据框非常陌生，它具有一个日期时间列和一个包含文本字符串（标题）的列。每个标题将是一个新行。

I'm very new to pandas data frame that has a date time column, and a column that contains a string of text (headlines). Each headline will be a new row.

我需要在x轴上绘制日期，而y轴需要包含标题出现在多少次上每个日期。

I need to plot the date on the x-axis, and the y-axis needs to contain how many times a headline occurs on each date.

因此，例如，一个日期可能包含3个标题。

So for example, one date may contain 3 headlines.

最简单的方法是这个？我根本不知道该怎么做。也许添加另一列，每行带有 1？如果是这样，您将如何做？

What's the simplest way to do this? I can't figure out how to do it at all. Maybe add another column with a '1' for each row? If so, how would you do this?

请向我指出任何可能有帮助的方向！

Please point me in the direction of anything that may help!

谢谢！

我尝试在y上绘制计数，但一直出现错误，我尝试创建一个用于计算行数的变量，但这没有

I have tried plotting the count on the y, but keep getting errors, I tried creating a variable that counts the number of rows, but that didn't return anything of use either.

我尝试添加带有标题计数的列

I tried add a column with the count of headlines

df_data['headline_count'] = df_data['headlines'].count

，然后我尝试了方法

df_data['count'] = df.groupby('headlines')['headlines'].transform('count')

使用Groupie时，出现错误

When I use groupie, i get an error of

KeyError: 'headlines'

输出应该只是一个图，该图重复数据帧中的日期重复了多少次（这表明存在多个y轴上的行）。并且x轴应该是观察到的日期。

The output should simply be a plot with how many times a date is repeated in the dataframe (which signals that there are multiple headlines) in the rows plotted on the y-axis. And the x-axis should be the date that the observations occurred.

推荐答案

尝试一下：

import numpy as np import matplotlib.pyplot as plt import pandas as pd A = pd.DataFrame(columns=["Date", "Headlines"], data=[["01/03/2018","Cricket"],["01/03/2018","Football"], ["02/03/2018","Football"],["01/03/2018","Football"], ["02/03/2018","Cricket"],["02/03/2018","Cricket"]] )

您的数据如下所示：

print (A) Date Headlines 0 01/03/2018 Cricket 1 01/03/2018 Football 2 02/03/2018 Football 3 01/03/2018 Football 4 02/03/2018 Cricket 5 02/03/2018 Cricket

现在通过操作对其进行分组：

Now do a group by operation on it:

data = A.groupby(["Date","Headlines"]).size() print(data) Date Headlines 01/03/2018 Cricket 1 Football 2 02/03/2018 Cricket 2 Football 1 dtype: int64

现在您可以绘图它使用以下代码：

You can now plot it using the below code:

# set width of bar barWidth = 0.25 # set height of bar bars1 = data.loc[(data.index.get_level_values('Headlines') =="Cricket")].values bars2 = data.loc[(data.index.get_level_values('Headlines') =="Football")].values # Set position of bar on X axis r1 = np.arange(len(bars1)) r2 = [x + barWidth for x in r1] # Make the plot plt.bar(r1, bars1, color='#7f6d5f', width=barWidth, edgecolor='white', label='Cricket') plt.bar(r2, bars2, color='#557f2d', width=barWidth, edgecolor='white', label='Football') # Add xticks on the middle of the group bars plt.xlabel('group', fontweight='bold') plt.xticks([r + barWidth for r in range(len(bars1))], data.index.get_level_values('Date').unique()) # Create legend & Show graphic plt.legend() plt.xlabel("Date") plt.ylabel("Count") plt.show()

希望这会有所帮助！